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Safi
58 lines
2.2 KiB
Markdown
58 lines
2.2 KiB
Markdown
# Reproducible Example
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A small document pipeline (parser, validator, processor, storage, API) with architecture notes and research notes. Six files, two languages, clear call relationships between modules.
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Run graphify on it and you get a knowledge graph showing how the modules connect, which functions call which, and how the architecture notes relate to the code.
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## Input files
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```
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raw/
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├── parser.py reads files, detects format, kicks off the pipeline
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├── validator.py schema checks, calls processor for text normalization
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├── processor.py keyword extraction, cross-reference detection
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├── storage.py persists everything, maintains the index
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├── api.py HTTP handlers that orchestrate the above four modules
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├── architecture.md design decisions and module responsibilities
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└── notes.md open questions and tradeoffs, written informally
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```
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## How to run it
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```bash
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pip install graphifyy && graphify install
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```
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Then open Claude Code in this directory and type:
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```
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/graphify ./raw
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```
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Takes under a minute. No PDF or image extraction, so it runs entirely on AST and markdown parsing with no token cost for semantic extraction.
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## What to expect
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The graph should show:
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- api.py as a hub node connected to all four modules
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- parser.py calling validator.py and storage.py
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- validator.py calling processor.py for normalize_text
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- processor.py calling storage.py for load_index and save_processed
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- architecture.md and notes.md linked to the code modules they discuss
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The community detection will likely cluster the four Python modules together and the two markdown files together, or split api.py into its own cluster given its high connectivity.
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God nodes will be storage.py (everything reads and writes through it) and api.py (connects to everything at the top level).
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## After it runs
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Ask questions in Claude Code and it answers from the graph:
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- "what calls storage directly?"
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- "what is the shortest path between parser and processor?"
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- "which module has the most connections?"
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- "what does the architecture doc say about the storage design?"
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The graph lives in graphify-out/ and persists across sessions.
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